This post explains how qualitative research uncovers why marginalized women in Pakistan are offline and how AI-enabled tools speed and strengthen that analysis. The primary keyword is "qualitative analysis of digital gender exclusion" and the audience is qualitative researchers, program designers, and policy teams working on digital inclusion. The payoff is actionable methods: how to run CBPR focus groups and co-design workshops, capture Urdu/Sindhi transcripts, and accelerate reflexive thematic analysis while preserving community ownership and data security.
Key Takeaways
According to the PLOS One study protocol published 20 August 2026, gendered social norms are the primary driver of why marginalized women in Azam Basti, Karachi, have limited access to phones and internet; the study will use participatory methods to co-design local solutions (PLOS One).
- PLOS One (20 August 2026) plans a community-based participatory study with an estimated sample of 36–45 participants across FGDs, interviews, and co-design workshops.
- According to the PLOS One authors and GSMA cited in the protocol, women in Pakistan were 38% less likely than men to own a mobile phone or access mobile internet in 2024.
- The PLOS One protocol reports Pakistan ranked 145 out of 146 countries on the Global Gender Gap Index in 2024, and a Pakistan Telecommunication Authority survey (2024) found 16% of female respondents and 23% of male respondents believed women should not use mobile phones at all.
- The project timeline in PLOS One schedules field recruitment from August to November 2026 and expects results beginning in late 2027.
What happened and how the study will measure it
Answer: The PLOS One protocol lays out a three-phase qualitative study to identify sociocultural barriers and co-design interventions to reduce digital gender exclusion in a low-income Karachi community.
According to PLOS One (20 August 2026), the study combines Technofeminism theory with community-based participatory research and includes: (1) a Community Advisory Committee, (2) focus group discussions and 4–5 in-depth interviews per participant group, and (3) three co-design workshops.
According to PLOS One (20 August 2026), data collection will use photo-elicitation and role-play to surface family norms, and transcripts will be produced in Urdu (and Sindhi where needed) and translated into English for reflexive thematic analysis using Braun and Clarke’s method.
Findings snapshot
| Date | Metric | Value | Implication |
|---|---|---|---|
| 2024 | GSMA Mobile Gender Gap (as cited in PLOS One) | Women 38% less likely to own mobile or access mobile internet | Structural access gap: interventions must target norms and affordability |
| 2024 | Global Gender Gap Index (World Economic Forum, as cited in PLOS One) | Pakistan ranked 145 of 146 | Broader gender inequality context shapes digital exclusion |
| Aug 20, 2026 | PLOS One study published | Study protocol and timeline published | Researchers can replicate methods and prepare ethical approvals |
| Feb 2026 to Jan 2028 | Project timeline (PLOS One) | Two-year project; recruitment Aug–Nov 2026; data by Apr 2027; analysis May 2027–Jan 2028 | Plan logistics and funding cycles accordingly |
| 2025 Competition | SSHRC funding (as reported in PLOS One) | $70, 626 | Scale expectations and budget constraints for similar CBPR projects |
Implications for qualitative researchers studying digital gender inclusion
Answer: The PLOS One protocol shows that addressing digital gender exclusion requires methods that go beyond surveys and include participatory, context-sensitive qualitative approaches.
According to PLOS One (20 August 2026), co-design with family gatekeepers and community leaders is central because household power dynamics, not only individual skills, shape women’s access to devices and internet.
According to PLOS One (20 August 2026), photo-elicitation and role-play are recommended to surface tacit norms and enable safe reflection; researchers should budget for bilingual transcription, translation, and community advisory co-analysis.
How Evidano helps
Problem: Bilingual transcripts and translation create delays
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
Solution: Use Evidano’s transcription and translation features with a custom dictionary for Urdu and Sindhi to reduce manual turnaround time while keeping community terminology accurate.
Contextual link: See the Evidano speech-to-text and translation pages for technical details.
Problem: Reflexive thematic analysis across stakeholder groups is time consuming
Solution: Evidano automates thematic extraction, produces code frequency tables, and supports cross-segment comparisons so teams can compare marginalized women, family gatekeepers, and community leaders in minutes instead of weeks.
Feature mapping: thematic and cross-segment analyses, code hierarchies, and co-occurrence networks speed Braun and Clarke style reflexive work while preserving researchers’ analytic control.
Contextual link: Learn more on the Evidano features page.
Problem: Community co-analysis requires transparent, shareable outputs
Solution: Evidano creates visualizations (word clouds, co-occurrence networks, hierarchical code maps) and exportable summaries researchers can review with a Community Advisory Committee for validation and member-checking.
Data security note: Evidano uses encrypted storage and does not use customer data to train third-party models; see data security.
Problem: Field teams need fast answers during iterative co-design workshops
Solution: Evidano’s AI chat over uploaded documents lets facilitators ask on-the-fly questions of transcripts and previous FGDs to adapt workshop prompts and test emerging hypotheses in real time.
Contextual link: Read about the Evidano AI chatbot capability for live research support.
FAQ: qualitative analysis of digital gender exclusion
How many participants are planned in the PLOS One study and why does that matter for qualitative analysis?
Answer: The PLOS One protocol plans approximately 36–45 participants across FGDs, interviews, and workshops, which is sized for theoretical saturation rather than statistical power.
Supporting detail: According to PLOS One (20 August 2026), FGDs will have 4–5 participants each, with 2 FGDs per participant group plus 4–5 in-depth interviews per group, and sample size will be finalized based on saturation.
Why use photo-elicitation and role-play for studying women's technology access?
Answer: Photo-elicitation and role-play surface tacit norms and enable participants to discuss sensitive topics indirectly, which improves depth of insight.
Supporting detail: According to PLOS One (20 August 2026), photo-elicitation uses 5–6 culturally curated images and a three-step ladder of questioning, while role-play reveals household decision-making dynamics in low-risk scenarios.
Can AI tools distort participant voice when used in qualitative analysis?
Answer: AI tools can introduce bias if used uncritically, but when combined with researcher reflexivity and community validation they accelerate analysis without replacing interpretation.
Supporting detail: PLOS One (20 August 2026) emphasizes co-analysis with a Community Advisory Committee to validate themes, and researchers should treat AI outputs as analytic aids to be reviewed and refined with community members.
When will the PLOS One study produce results and how should researchers plan?
Answer: The PLOS One protocol expects results beginning in late 2027, so researchers planning similar CBPR timelines should budget 12–18 months for data collection and 6–9 months for analysis and dissemination.
Supporting detail: According to PLOS One (20 August 2026), recruitment runs Aug–Nov 2026, data collection completes by April 2027, and analysis and knowledge mobilization occur May 2027–Jan 2028.
Conclusion & Next Steps
Answer: The PLOS One protocol provides a replicable qualitative blueprint for diagnosing and co-designing solutions to digital gender exclusion that centers household power dynamics and community leadership.
Researchers and program teams should plan for bilingual transcription, participant co-analysis, and iterative co-design workshops as outlined in PLOS One (20 August 2026), and consider AI tools to speed synthesis while preserving reflexivity.
If you want to pilot an AI-accelerated workflow that supports Urdu/Sindhi transcription, thematic and cross-segment analyses, and community-facing visualizations, Try Evidano for free.
Topics
- qualitative analysis of digital gender exclusion
- digital gender inclusion qualitative research
- gender digital divide Pakistan
- AI-enabled qualitative analysis
Keep reading
- Commentary on NewsDigital Gender Inclusion: Qualitative Research GuideStudy Pakistan’s gendered internet gap with digital gender inclusion qualitative research, CBPR methods, and AI-enabled synthesis; practical steps and tools.
- Commentary on NewsCo-designing Digital Gender Inclusion: Qualitative Research MethodsHow to use qualitative methods to study digital gender inclusion: methods from a PLOS One protocol, key stats, and AI-enabled analysis workflows for researchers.
- Commentary on NewsAI-enabled Qualitative Analysis: Digital Gender ExclusionApply AI-enabled thematic methods to qualitative analysis of digital gender exclusion: actionable steps from a PLOS One study protocol on Pakistan, for researchers and practitioners.